Articles | Volume 8, issue 5
https://doi.org/10.5194/gmd-8-1285-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-8-1285-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
04 May 2015
Model description paper |
| 04 May 2015
A generic approach to explicit simulation of uncertainty in the NEMO ocean model
J.-M. Brankart
CORRESPONDING AUTHOR
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
G. Candille
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
F. Garnier
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
C. Calone
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
A. Melet
Princeton University/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
P.-A. Bouttier
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
P. Brasseur
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
J. Verron
CNRS/Univ. Grenoble Alpes, Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE) UMR 5183, Grenoble, 38041, France
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G. Candille, J.-M. Brankart, and P. Brasseur
Ocean Sci., 11, 425–438, https://doi.org/10.5194/os-11-425-2015, https://doi.org/10.5194/os-11-425-2015, 2015
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A realistic ocean circulation model is adapted to explicitly simulate model uncertainties and an ensemble data assimilation -stochastic perturbations, altimetric data and 4-D observation operator- is developed in order to control the Gulf Stream dynamic. The performance of the ensemble system is measured through probabilistic approach; the update then adjusts the bias and the dispersion of the ensemble (reliability) and reduces the uncertainty by 30% (resolution) for the SSH variable.
M. Meinvielle, J.-M. Brankart, P. Brasseur, B. Barnier, R. Dussin, and J. Verron
Ocean Sci., 9, 867–883, https://doi.org/10.5194/os-9-867-2013, https://doi.org/10.5194/os-9-867-2013, 2013
G. Candille, J.-M. Brankart, and P. Brasseur
Ocean Sci., 11, 425–438, https://doi.org/10.5194/os-11-425-2015, https://doi.org/10.5194/os-11-425-2015, 2015
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A realistic ocean circulation model is adapted to explicitly simulate model uncertainties and an ensemble data assimilation -stochastic perturbations, altimetric data and 4-D observation operator- is developed in order to control the Gulf Stream dynamic. The performance of the ensemble system is measured through probabilistic approach; the update then adjusts the bias and the dispersion of the ensemble (reliability) and reduces the uncertainty by 30% (resolution) for the SSH variable.
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Nonlin. Processes Geophys., 22, 233–248, https://doi.org/10.5194/npg-22-233-2015, https://doi.org/10.5194/npg-22-233-2015, 2015
A. Vidard, P.-A. Bouttier, and F. Vigilant
Geosci. Model Dev., 8, 1245–1257, https://doi.org/10.5194/gmd-8-1245-2015, https://doi.org/10.5194/gmd-8-1245-2015, 2015
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This paper presents the tangent and adjoint models for the NEMO ocean modelling framework. They are useful tools for sensitivity and stability analysis. The implementation choices and the validation of the code is presented as well as a selection of applications.
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Geosci. Model Dev., 8, 69–86, https://doi.org/10.5194/gmd-8-69-2015, https://doi.org/10.5194/gmd-8-69-2015, 2015
S. Metref, E. Cosme, C. Snyder, and P. Brasseur
Nonlin. Processes Geophys., 21, 869–885, https://doi.org/10.5194/npg-21-869-2014, https://doi.org/10.5194/npg-21-869-2014, 2014
M. Meinvielle, J.-M. Brankart, P. Brasseur, B. Barnier, R. Dussin, and J. Verron
Ocean Sci., 9, 867–883, https://doi.org/10.5194/os-9-867-2013, https://doi.org/10.5194/os-9-867-2013, 2013
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Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
EGUsphere, https://doi.org/10.5194/egusphere-2024-613, https://doi.org/10.5194/egusphere-2024-613, 2024
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Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
EGUsphere, https://doi.org/10.5194/egusphere-2024-95, https://doi.org/10.5194/egusphere-2024-95, 2024
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Global climate models do not reliably simulate sea-level change arising from ice sheet-ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations, and study how models respond to a range of perturbations in climate and ice-sheet geometry. The 2nd Marine Ice Sheet Ocean Model Intercomparison Project, will continue to lay the groundwork for including ice sheet-ocean interactions in global scale, IPCC class models.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-237, https://doi.org/10.5194/gmd-2023-237, 2024
Revised manuscript accepted for GMD
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Qian Wang, Fei Chai, Yang Zhang, Yinglong Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-236, https://doi.org/10.5194/gmd-2023-236, 2024
Revised manuscript accepted for GMD
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We coupled an unstructured hydro model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model, and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
EGUsphere, https://doi.org/10.5194/egusphere-2023-1876, https://doi.org/10.5194/egusphere-2023-1876, 2023
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Harness AI for better ocean insights. BGC-Argo floats collect deep ocean data, yet forecasting vital nutrient levels is a challenge. Our novel AI approach, PPCon, learns from Argo float measurements and provides improved nutrient predictions. This enhances our understanding of ocean dynamics and nutrient distribution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
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We describe a method to relate the fluxes of heat and fresh water at the sea surface, to the resulting distribution of sea water among categories such as warm and salty, cold and salty, etc. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
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We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
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Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
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Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
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We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
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In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
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Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
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An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
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Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
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Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
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The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
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4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Cited articles
Achatz, U., Löbl, U., Dolaptchiev, S. I., and Gritsun, A.: Fluctuation-dissipation supplemented by nonlinearity: a climate-dependent subgrid-scale parameterization in low-order climate models, J. Atmos. Sci., 70, 1833–1846, 2013.
Arhonditsis, G. B., Perhar, G., Zhang, W., Massos, E., Shi, M., and Das, A.: Addressing equifinality and uncertainty in eutrophication models, Water Resour. Res., 44, W01420, https://doi.org/10.1029/2007WR005862, 2008.
Béal, D., Brasseur, P., Brankart, J.-M., Ourmières, Y., and Verron, J.: Characterization of mixing errors in a coupled physical biogeochemical model of the North Atlantic: implications for nonlinear estimation using Gaussian anamorphosis, Ocean Sci., 6, 247–262, https://doi.org/10.5194/os-6-247-2010, 2010.
Berloff, P.: On rectification of randomly forced flows, J. Mar. Res., 63, 497–527, https://doi.org/10.1357/0022240054307894, 2005.
Bertino, L., Evensen, G., and Wackernagel, H.: Sequential data assimilation techniques in oceanography, Int. Stat. Rev., 71, 223–241, 2003.
Brankart, J.-M.: Impact of uncertainties in the horizontal denisty gradient upon low resolution global ocean modelling, Ocean Model., 66, 64–76, 2013.
Brankart, J.-M., Testut, C.-E., Béal, D., Doron, M., Fontana, C., Meinvielle, M., Brasseur, P., and Verron, J.: Towards an improved description of ocean uncertainties: effect of local anamorphic transformations on spatial correlations, Ocean Sci., 8, 121–142, https://doi.org/10.5194/os-8-121-2012, 2012.
Brier, G. W.: Verification of forecasts expressed in terms of probability, Mon. Weather Rev., 78, 1–3, 1950.
Buizza, R., Miller, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteor. Soc., 125, 2887–2908, 1999.
Candille, G. and Talagrand, O.: Evaluation of probabilistic prediction systems for a scalar variable, Q. J. Roy. Meteor. Soc., 131, 2131–2150, 2005.
Evensen, G.: Sequential data assimilation with a non linear quasigeostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10143–10162, 1994.
Frederiksen, J., O'Kane, T., and Zidikheri, M.: Stochastic subgrid parameterizations for atmospheric and oceanic flows, Phys. Scripta, 85, 068202, https://doi.org/10.1088/0031-8949/85/06/068202, 2012a.
Frederiksen, J. S., O'Kane, T. J., and Zidikheri, M. J.: Stochastic subgrid parameterizations for atmospheric and oceanic flows, Phys. Scripta, 85, 068202, https://doi.org/10.1088/0031-8949/85/06/068202, 2012b.
Greatbatch, R. J. and Zhai, X.: Influence of assimilated eddies on the large-scale circulation in a model of the northwest Atlantic Ocean, Geophys. Res. Lett., 33, L02614, https://doi.org/10.1029/2005GL025139, 2006.
Greatbatch, R. J., Sheng, J., Eden, C., Tang, L., Zhai, X., and Zhao, J.: The semi-prognostic method, Cont. Shelf. Res., 24, 2149–2165, 2004.
Grooms, I. and Majda, A. J.: Efficient stochastic superparameterization for geophysical turbulence, P. Natl. Acad. Sci. USA, 110, 4464–4469, 2013.
Juricke, S., Lemke, P., Timmermann, R., and Rackow, T.: Effects of stochastic ice strength perturbation on Arctic finite element sea ice modeling, J. Climate, 26, 3785–3802, 2013.
Kitsios, V., Frederiksen, J., and Zidikheri, M.: Scaling laws for parameterisations of subgrid eddy-eddy interactions in simulations of oceanic circulations, Ocean Model., 68, 88–105, 2013.
Le Quéré, C., Harrison, S. P., Prentice, I. C., Buitenhuis, E. T., Aumont, O., Bopp, L., Claustre, H., Cotrim Da Cunha, L., Geider, R., Giraud, X., Klaas, C., Kohfeld, K. E., Legendre, L., Manizza, M., Platt, T., Rivkin, R. B., Sathyendranath, S., Uitz, J., Watson, A. J., and Wolf-Gladrow, D.: Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models, Glob. Change Biol., 11, 2016–2040, 2005.
Lévy, M., Gavart, M., Mémery, L., Caniaux, G., and Paci, A.: A four-dimensional mesoscale map of the spring bloom in the northeast atlantic (POMME experiment): results of a prognostic model, J. Geophys. Res., 110, C07S21, https://doi.org/10.1029/2004JC002588, 2005.
Madec, G. and Imbard, M.: A global ocean mesh to overcome the north pole singularity, Clim. Dynam., 12, 381–388, 1996.
Madec, G. and the NEMO team: NEMO ocean engine, Note du Pôle de modélisation 27, Institut Pierre-Simon Laplace (IPSL), France, ISSN 1288–1619, 2008.
Meinvielle, M., Brankart, J.-M., Brasseur, P., Barnier, B., Dussin, R., and Verron, J.: Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation, Ocean Sci., 9, 867–883, https://doi.org/10.5194/os-9-867-2013, 2013.
Palmer, T. N.: A nonlinear dynamical perspective on model error: A proposal for non-local stochastic-dynamic parametrization in weather and climate prediction models, Q. J. Roy. Meteorol. Soc., 127, 279–304. https://doi.org/10.1002/qj.49712757202, 2001.
Palmer, T. N., Shutts, G., Hagedorn, R., Doblas-Reyes, F., Jung, T., and Leutbecher, M.: Representing model uncertainty in weather and climate prediction, Annu. Rev. Earth Pl. Sc., 33, 163–193, 2005.
Palmer, T. N., Buizza, R., Doblas-Reyes, F., Jung, T., Leutbecher, M., Shutts, G. J., Steinheimer, M., and Weisheimer A.: Stochastic parametrization and model uncertainty, ECMWF Tech. Memo. 598, 42 pp., 2009.
Palmer, T. N., Düben, P., and McNamara, H.: Stochastic modelling and energy-efficient computing for weather and climate prediction, Phil. Trans. A, 372, https://doi.org/10.1098/rsta.2014.0118, 2014.
Penduff, T., Juza, M., Barnier, B., Zika, J., Dewar, W. K., Treguier, A.-M., Molines, J.-M., and Audiffren, N: Sea-level expression of intrinsic and forced ocean variabilities at interannual time scales, J. Climate, 24, 5652–5670, 2011.
Shutts, G.: A kinetic energy backscatter algorithm for use in ensemble prediction systems, Q. J. Roy. Meteorol. Soc., 131, 3079–3102, 2005.
Skandrani, C., Brankart, J.-M., Ferry, N., Verron, J., Brasseur, P., and Barnier, B.: Controlling atmospheric forcing parameters of global ocean models: sequential assimilation of sea surface Mercator-Ocean reanalysis data, Ocean Sci., 5, 403–419, https://doi.org/10.5194/os-5-403-2009, 2009.
Toth, Z., Talagrand, O., Candille, G., and Zhu, Y.: Probability and ensemble forecasts, in: Forecast Verification: a Practitioner's Guide in Atmospheric Science, edited by: Jolliffe I. and Stephenson, D. B., Wiley, UK, 137–163, 2003.
Wilks, D. S.: Effects of stochastic parametrizations in the Lorenz'96 system, Q. J. Roy. Meteor. Soc., 131, 389–407, 2005.
Short summary
In this paper, a simple and generic implementation approach is presented, with the aim of transforming a deterministic ocean model (like NEMO) into a probabilistic model. With this approach, several kinds of stochastic parameterizations are implemented to simulate the non-deterministic effect of unresolved processes, unresolved scales, and unresolved diversity. The method is illustrated with three applications, showing that uncertainties can produce a major effect in the model simulations.
In this paper, a simple and generic implementation approach is presented, with the aim of...
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